Triple
T4566670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron |
E121925
|
entity |
| Predicate | typicalFeminineForm |
P17779
|
FINISHED |
| Object | Baroness |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Baroness | Statement: [Baron, typicalFeminineForm, Baroness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFeminineForm Context triple: [Baron, typicalFeminineForm, Baroness]
-
A.
hasFeminineFormInSomeLanguages
Indicates that the referenced entity has a distinct feminine grammatical or lexical form in at least one language.
-
B.
genderedFormOf
chosen
Indicates that one term is a gender-specific variant or inflected form corresponding to another, more neutral or differently gendered term.
-
C.
genderNeutralForm
Indicates that one entity is a gender-neutral linguistic form or expression corresponding to another, more gendered form.
-
D.
hasFeminineFormInCzechAndSlovak
Indicates that an entity has a specifically feminine grammatical or lexical form in the Czech and Slovak languages.
-
E.
typicalForm
Indicates that one entity represents the standard, characteristic, or most common form or shape in which another entity typically appears or is realized.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd589e35808190aa609bb04b128dbe |
completed | March 20, 2026, 2:24 p.m. |
| PD | Predicate disambiguation | batch_69bd5227063c8190973155a875b013a7 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.